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The purpose of this paper is to explore the changes of the scale of urban tourists in mainland China under the impact of COVID-19 and, specifically, the following questions: how did the scale of domestic tourists change nationwide and in the seven geographic regions? What are the differences in the changes among the seven geographic regions? What are the changes in the hot spot areas and spatial clustering of domestic tourists across the country?

Using the data of domestic tourist arrivals in 337 cities in mainland China from 2018 to 2021, this research analyzes the absolute differences and relative differences in the scale of domestic tourists nationwide and in seven geographic divisions with the help of indicators such as range analysis, standard deviation, coefficient of variation and Herfindahl–Hirschman Index and explores the changes in the hot spot areas and spatial concentration degree of the spatial scale of domestic tourists nationwide under the influence of the epidemic using kernel density analysis and spatial auto-correlation analysis.

The absolute differences in all seven geographical divisions continue to increase during 2018–2021. The domestic tourism in southwest China is extremely uneven. Absolute differences in the northwest and northeast regions are relatively small, and the development in attracting domestic tourists is more balanced. Relative differences in southwest China are comparatively large, with the trend of uneven development being obvious. The northeast, northwest and eastern regions of China are small, and the development is more balanced. The popularity of domestic tourism in the Beijing–Tianjin–Hebei region, as well as the Yangtze River Delta region, continues to decline and then pick up in 2021. The inland southwest region became a new domestic tourism hot spot in 2021. The size of domestic tourists from 2018 to 2021 in mainland China cities shows a significant positive spatial correlation, and there is a spatial agglomeration phenomenon, but some regional agglomeration types change from 2018 to 2021.

The impact of the epidemic on the number and spatial scale of domestic tourism in China has been clarified, which makes up for the comparison of domestic tourism changes before and after the epidemic. A clear understanding of the changes in the number and spatial scale of domestic tourists in different regions after the epidemic is conducive to the development of domestic tourism revitalization strategies in accordance with the actual situation of each province and promotes the internal circulation of Chinese tourism.

This paper tries to clarify the quantitative scale of domestic tourism in different regions after the epidemic, which is conducive to the development of domestic tourism revitalization strategies in cities in different regions according to regional characteristics and the actual situation of each province and to promote the healthy operation of the internal circulation of tourism in China. This paper also tries to show the changes of domestic tourism market hot spots, agglomeration conditions changes before and after the outbreak and the clarity of tourists’ preference space changes.

Scale of domestic tourists; Absolute difference; Relative difference; Spatial hot spot distribution; Spatial agglomeration change

本文旨在探寻疫情影响下中国大陆城市游客规模演化规律, 具体而言, 疫情影响下, 全国及七大地理分区的国内游客量规模变化如何？七大地理地区的变化有何差异？以及疫情影响下, 全国国内游客空间规模的热点区域和空间集聚程度有何变化？

利用2018-2021年中国大陆337各城市的国内游客量数据, 借助极差、标准差、变异系数、赫芬达尔指等指标分析全国及七大地理分区国内游客规模的绝对差异和相对差异; 借助核密度分析、空间自相关分析等ArcGIS分析工具, 探寻疫情影响下全国国内游客空间规模的热点区域和空间集聚程度的变化情况。

①绝对差异方面, 七大地理分区的绝对差异均持续增大。西南地区的游客量的绝对差异巨大, 国内游发展极不均衡。西北地区、东北地区绝对差异相对较小, 在吸引国内游客方面发展较为均衡。②相对差异方面, 西南地区的国内游发展相对差异较大, 发展不均衡趋势明显; 东北地区、西北地区、华东地区的国内游发展相对差异较小, 发展较为均衡。③热点区域变化方面, 京津冀地区、长三角地区的国内旅游热度持续下降, 在2021年有所回升; 内陆西南地区在2021年成为新的国内游热点区域。④2018年至2021年城市国内游客量规模均呈现出显著的空间正相关的关系, 存在着空间集聚现象, 但部分区域集聚类型在2018到2021年间发生变化。

①理论意义：明晰了疫情对中国国内旅游人次的数量规模和空间规模的影响, 弥补了当前疫情前后国内旅游业变化对比的研究; 阐明了疫情前后中国城市国内游客空间格局的变化, 拓展了研究情景, 丰富了中国旅游业时空变化的相关研究。②实践意义：明晰了疫后不同地区国内旅游人次的数量规模和空间规模变化情况, 以及国内旅游市场热点变化和游客空间偏好变化, 有利于各地区城市对症下药, 制定符合各省份实际情况的国内旅游业振兴策略, 促进中国旅游业内循环。

This paper aims to study the temporal and spatial variation of vegetation and the influence of climate change on vegetation coverage in the Yellow River basin, China. The current study aimed to evaluate the role of a series of government-led environmental control projects in restoring the ecological environment of the Yellow River basin.

This paper uses unary linear regression, Mann–Kendall and wavelet analyses to study the spatial–temporal variations of vegetation and the response to climate changes in the Yellow River, China.

The results showed that for the past 17 years, not only the mean annual increase rate of the Normalized Difference Vegetation Index (NDVI) was 0.0059/a, but the spatial heterogeneity also yields significant results. The vegetation growth in the southeastern region was significantly better than that in the northwestern region. The variation period of the NDVI in the study area significantly shortened, and the most obvious oscillation period was half a year, with two peaks in one year. In addition, there are positive and negative effects of human activities on the change of vegetation cover of the Loess Plateau. The project of transforming cultivated land to forest and grassland promotes the increase of vegetation cover of the Loess plateau. Unfortunately, the regional urbanization and industrialization proliferated, and the overloading of grazing, deforestation, over-reclamation, and the exploitation and development of the energy area in the grassland region led to the reduction of the NDVI. Fortunately, the positive effects outweigh the negative ones.

This paper provides a comprehensive insight to analysis of the vegetation change and the responses of vegetation to climate change, with special reference to make the planning policy of ecological restoration. This paper argues that ecological restoration should be strengthened in areas with annual precipitation less than 450 mm.

Green space is one of the main measures to alleviate urban heat islands (UHI). The transformation mechanism of daytime and nighttime scale sensitivity of vegetation coverage to reduce the UHI effect in a daily cycle has been unclear. As a result, we propose a scale sensitivity measurement algorithm to study the spatial and temporal response relationship between UHI and green coverage. Based on the scale theory of landscape ecology and the method of geostatistical analysis, we adopted ArcGIS, MATLAB, SPSS, and other data processing software as well as a large amount of measured and high-resolution satellite imagery data of Beijing and Tianjin to quantitatively study their spatial scale sensitivity and daily variation features of urban green spaces to reduce summer UHI. The results show that first, the green coverage rate and the UHI intensity experience positive and negative correlations during the daytime, and negative correlations at night. When the correlation coefficient is significant, there is a linear relationship between the UHI intensity and the core green rate. Second, the reduction of the UHI by green spaces displays spatial and temporal change scale sensitivity characteristics. The radius scale of daytime sensitivity is 15m, and the radius scale of nighttime sensitivity is 60m. The study's conclusion enriches the theoretical parameters of landscape ecological scales and patterns, and provides spatial and temporal scales for systematic planning of green space to reduce UHI.

This paper aims to explore the spatio-temporal patterns of Chinese foreign direct investment (FDI) since the inception of the Belt and Road Initiative (BRI) in 2013 as an extended version of geographically weighted regression.

The panel data are used to examine spatial and temporal dynamics of the magnitude and the direction of China's outward FDI stock and its flow from 2011 to 2015 at a country level. Using the geographically and temporally weighted regression (GTWR), spatio-temporal distribution of FDI is explained through Logistic Performance Index, the size of gross domestic product (GDP), Shipping Linear Connectivity Index and Container Port Throughput.

A comparative analysis between participating and non-participating countries in the BRI shows that the size of GDP and Container Port Throughput of the participating countries have a positive effect on the increases of China's outward FDI Stock to Asia especially after 2013, while non-participating countries, such as North America, Western Europe and Western Africa, have no significant effect on it before and after the implementation of the BRI.

The findings, however, will not necessarily provide insight into the needs of China's outward FDI in certain countries to develop their economy. The findings provide the evidence to inform policy making to help identify the winners and losers of the investment, scale and direction of investment and the key drivers that shape the distributive investment patterns globally.

The study provides the empirical evidence to inform investment policy and strategic realignment by quantifying scale, direction and drivers that shape the spatio-temporal shifts of China's FDI.

The analysis also guides the Chinese government improve bilateral trade, build infrastructure and business partnerships with preferential countries participating in the BRI.

There is an urgent need to adopt a new perspective to unfold the spatial temporal complexity of FDI that incorporates space and time dependencies, and the drivers of the situated context to model their effects on FDI. The model is based on GTWR and an extended geographically weighted regression (GWR) allowing the simultaneous analysis of spatial and temporal decencies of exploratory variables.

This discussion essay describes three methodological models of comparative analysis and tests a dialogue between Bartolini, Bray, and Bonilla Molina. Bartolini explores a model that combines dimensions of spatial and temporal variation noting the emphasis dedicated to synchronous cross-sectional investigation, as well as the need to think of time as a dimension of variation, as history. Bartolini summarizes the sociological and historical literature creating a data matrix to which he adds a dimension of time and outlines the case study and development of the case, the development trend, the great development theory, and a synchronous comparison of development. Bray adds items to a greater degree of specificity ranging from the spatial dimension with specific geographical units organized by varying degrees, types, and levels. The comparative analysis of the multilevel schematic occurs by the combination of: geographic levels, location from macro to micro; nonspatial population levels of large ethnic diversity, religion and gender as well as aspects of education and society including teachers, curriculum, finance, management, education, and work. Molina Bonilla presents a dynamic multidimensional model that combines all the macro and micro dimensions of education: school as a political project and as a continent and a country on the planet; as a teaching–learning process from citizenship and democracy; as a process involving students, teachers, and parents; and as a product where the spatial and temporal dimensions from the geopolitical merge into a dynamic hub that crosses stories, capital, and labor. The latter, created to assess quality, is a synthesis of the theoretical and methodological as it provides a multitude of benefits for successful comparative analysis in today’s global and international context of education.

This paper aims to investigate the basin-scale features and mechanisms of the synoptic variation of Yellow Sea Warm Current (YSWC) in winter.

Both in situ current observation and numerical model (MITgcm) were conducted to investigate the synoptic variation of YSWC. The model was well validated and the simulated results were analyzed.

The YSWC shows a much stronger synoptic variation than its mean in winter with strong variation mainly in the deep central YS. The synoptic variation of YSWC is associated a counterclockwise rotary wave as a response to the strong northerly wind bursts. Strong northerly wind generates a large sea surface height (SSH) drop in the Bohai Sea and northern YS. Then, the SSH rotates in a counterclockwise manner. About 18 h later, strong eastward SSH gradient is formed, generating a northward current through geostrophic balance.

The mechanisms analysis shows that the synoptic variation of YSWC is intrinsically linked to SSH as a response to the synoptic varying winter monsoon. This study provides an insight into the spatial and temporal evolution of the oceanic response to strong northerly wind in winter.

The purpose of this paper is to better understand landscape dynamics in arid and semi‐arid environments. Land degradation has recently become an important issue for land management in western China. The oasis ecosystem is especially sensitive to environmental disturbances, such as abnormal/extreme precipitation events, variations in the water supply from the upper watersheds, fluctuations in temperature, etc. Satellite remote sensing of terrestrial ecosystems can provide us with the temporal dynamics and spatial distributions of green cover over large areas of landscape. Seasonal green cover data are especially important in assessing landscape health (e.g. desertification, rate of urban sprawl, natural disturbances) in arid and semi‐arid regions. In this study, green cover data are derived from vegetation indices retrieved from moderate resolution imaging spectroradiometer (MODIS) sensors onboard the satellite Terra.

Satellite images recorded during the period from April 2000 to December 2005 are analyzed and the spatial distribution and temporal changes of the Ejin Oasis quantified.

This study shows that it is possible to derive important parameters linked to landscape sensitivity from MODIS and the derived imagery, such as normalized difference vegetation index (NDVI) time‐series data. Such a MODIS‐based time‐series monitoring system is particularly useful in arid and semi‐arid environments. The results of landscape sensitivity analysis prove the effectiveness of the method in assessing landscape sensitivity from the years 2001‐2005.

The novel strategy used in this investigation is based on the T‐S fuzzy model, which is in turn based on fuzzy theory and fuzzy operations.

Simulation results based on fuzzy models will help to improve the monitoring techniques used to evaluate land degradation and to estimate the newest tendency in landscape green cover dynamics in the Ejin Oasis.

Investigations of urban public services remain confined to western settings while research on urban public services in non-western cities focuses mainly on the availability and delivery of basic services. Using the case study of Calcutta, this study is an empirical investigation of the evolution, spatial distribution, and changes in spatial patterns of public libraries for the period 1850–1991. It seeks to demonstrate the provision and accessibility to public libraries at the intraurban scale thereby extending research of urban service delivery to a non-western city. Within the context of urban service delivery – who benefits and why, the location of libraries in three time periods are analyzed. The study finds that the urban morphology of the colonial city continues to exert a strong influence on the growth and spatial distribution of public libraries. Empirical evidence suggests that there is no locational bias based on physical accessibility in the distribution of public libraries. No progressive or regressive spatial arrangement based on socioeconomic variables is indicated.

Air quality, noise and proximity to urban infrastructure can arguably have an important impact on the quality of life. Environmental quality (the price of good health) has become a central tenet for consumer choice in urban locales when deciding on a residential neighbourhood. Unlike the market for most tangible goods, the market for environmental quality does not yield an observable per unit price effect. As no explicit price exists for a unit of environmental quality, this paper aims to use the housing market to derive its implicit price and test whether these constituent elements of health and well-being are indeed capitalised into property prices and thus implicitly priced in the market place.

A considerable number of studies have used hedonic pricing models by incorporating spatial effects to assess the impact of air quality, noise and proximity to noise pollutants on property market pricing. This study presents a spatial analysis of air quality and noise pollution and their association with house prices, using 2,501 sale transactions for the period 2013. To assess the impact of the pollutants, three different spatial modelling approaches are used, namely, ordinary least squares using spatial dummies, a geographically weighted regression (GWR) and a spatial lag model (SLM).

The findings suggest that air quality pollutants have an adverse impact on house prices, which fluctuate across the urban area. The analysis suggests that the noise level does matter, although this varies significantly over the urban setting and varies by source.

Air quality and environmental noise pollution are important concerns for health and well-being. Noise impact seems to depend not only on the noise intensity to which dwellings are exposed but also on the nature of the noise source. This may suggest the presence of other externalities that arouse social aversion. This research presents an original study utilising advanced spatial modelling approaches. The research has value in further understanding the market impact of environmental factors and in providing findings to support local air zone management strategies, noise abatement and management strategies and is of value to the wider urban planning and public health disciplines.

People call the police and want them to handle a variety of matters besides criminal ones. The city is divided into various communities with different functions and routine activity patterns. This paper examines how calls for police service vary with routine activities and time between two residential areas that are opposites on the quality of life spectrum. The study site is Charlotte, North Carolina, and the data are the calls for service received by the police department during 1986.